genRCT.surv: Generalizing the average treatment effect (ATE) from the...

In idasomm/genRCT: Generalizing the average treatment effect (ATE) from the trial using observational studies (OS)

Generalizing the average treatment effect (ATE) from the trial using observational studies (OS) for survival outcomes

Description

Provides estimation and inference for the average treatment effect (ATE), generalizing from a randomized controlled trial (RCT) to a target population leveraging observational studies. The method of sieves can be used for the estimation of sampling score and outcome models.

Usage

genRCT.surv(
  Y.trial,
  d.trial,
  A.trial,
  X.trial,
  X.rwe,
  tau,
  eta.vec = c(0, 0.001, 0.005),
  n.boot = 100,
  conf.level = 0.05,
  seed = NULL,
  verbose = TRUE
)

Arguments

Y.trial	Observed outcome from a trial; vector of size n (trial sample size).
d.trial	The event indicator, normally 1 = event, 0 = censored; vector of size n.
A.trial	Treatment received from a trial; vector of size n.
X.trial	Matrix of p baseline covariates from a trial; dimension n by p.
X.rwe	Matrix of p baseline covariates from OS; dimension m by p.
tau	| A vector of truncation time for defining restricted mean survival time; e.g., seq(10, 50, by = 10)
n.boot	A numeric value indicating the number of bootstrap samples used. This is only relevant if inference = TRUE. Default is 100.
conf.level	The level of bootstrap confidence interval; Default is 0.05.
seed	An optional integer specifying an initial randomization seed for reproducibility. Default is NULL, corresponding to no seed.
verbose	A logical value indicating whether intermediate progress messages should be printed. Default is TRUE.

Value

Return a list containing:

rmst

idasomm/genRCT documentation built on April 15, 2023, 7:16 a.m.